This notebook contains a set of analyses for analyzing rahdo’s boardgamegeek collection. The bulk of the analysis is focused on building a user-specific predictive model to predict the games that the specified user is likely to own. This enables us to ask questions like, based on the games the user currently owns, what games are a good fit for their collection? What upcoming games are they likely to purchase?
We can look at a basic description of the number of games that the user owns, has rated, has previously owned, etc.
What years has the user owned/rated games from? While we can’t see when a user added or removed a game from their collection, we can look at their collection by the years in which their games were published.
We can look at the most frequent types of categories, mechanics, designers, and artists that appear in a user’s collection.
We’ll examine predictive models trained on a user’s collection for games published through 2020. How many games has the user owned/rated/played in the training set (games prior to 2020)?
username | dataset | period | games_owned | games_rated |
rahdo | training | published before 2020 | 1,240 | 307 |
rahdo | validation | published 2020 | 109 | 40 |
rahdo | test | published after 2020 | 118 | 50 |
The main outcome we will be modeling for the user is owned, which refers to whether the user currently owns or has a previously owned a game in their collection. Our goal is to train a predictive model to learn the probability that a user will add a game to their collection based on its observable features. This amounts to looking at historical data and looking to find patterns that exist between features of games and games present in the user’s collection.
One of the models we trained was a decision tree, which looks for decision rules that can be used to separate games the user owns from games they don’t. The resulting model produces a decision corresponding to yes or no statements: to explain why the model predicts the user to own game, we start at the top of the tree and follow the rules that were learned from the training data.
Note: the tree below has been further pruned to make it easier to visualize.
Decision trees are highly interpretible models that are easy to train and can identify important interactions and nonlinearities present in the data. Individual trees have the drawback of being less predictive than other common models, but it can be useful to look at them to gain some understanding of key predictors and relationships found in the training data.
We can examine coefficients from another model we trained, which is a logistic regression with elastic net regularization (which I will refer to as a penalized logistic regression). Positive values indicate that a feature increases a user’s probability of owning/rating a game, while negative values indicate a feature decreases the probability. To be precise, the coefficients indicate the effect of a particular feature on the log-odds of a user owning a game.
Why did the model identify these features? We can make density plots of the important features for predicting whether the user owned a game. Blue indicates the density for games owned by the user, while grey indicates the density for games not owned by the user.
Binary predictors can be difficult to see with this visualization, so we can also directly examine the percentage of games in a user’s collection with a predictor vs the percentage of all games with that predictor.
% of Games with Feature | ||||
username | Feature | User_Collection | All_Games | Ratio |
rahdo | Artist Klemens Franz | 5.2% | 0.3% | 16.31 |
rahdo | Renegade Game Studios | 3.2% | 0.2% | 14.32 |
rahdo | Stronghold Games | 4.4% | 0.4% | 12.30 |
rahdo | Worker Placement | 18.9% | 2.3% | 8.09 |
rahdo | City Building | 12.3% | 1.7% | 7.44 |
rahdo | Rio Grande Games | 8.6% | 1.5% | 5.81 |
rahdo | Economic | 21.2% | 6.0% | 3.51 |
rahdo | Set Collection | 31.9% | 12.1% | 2.63 |
rahdo | Dice Rolling | 24.3% | 28.7% | 0.85 |
rahdo | Take That | 4.3% | 5.2% | 0.82 |
rahdo | Miniatures Game | 2.8% | 5.0% | 0.57 |
rahdo | Abstract Strategy | 3.4% | 7.5% | 0.45 |
rahdo | Negotiation | 1.0% | 3.3% | 0.32 |
rahdo | Roll Spin And Move | 0.8% | 7.1% | 0.11 |
rahdo | Childrens Game | 0.4% | 8.5% | 0.05 |
rahdo | Wargame | 0.7% | 19.8% | 0.04 |
Before predicting games in upcoming years, we can examine how well the model did and what games it liked in the training set. In this case, we used resampling techniques (cross validation) to ensure that the model had not seen a game before making its predictions.
Displaying the 100 games from the training set with the highest probability of ownership, highlighting in blue games the user has owned.
Rank | Published | ID | Name | Pr(Owned) | Owned |
1 | 2013 | 143693 | Glass Road | 0.997 | yes |
2 | 2009 | 39683 | At the Gates of Loyang | 0.996 | yes |
3 | 2011 | 70149 | Ora et Labora | 0.994 | yes |
4 | 2010 | 70512 | Luna | 0.994 | yes |
5 | 2008 | 35677 | Le Havre | 0.991 | yes |
6 | 2015 | 175878 | 504 | 0.988 | yes |
7 | 2016 | 167791 | Terraforming Mars | 0.986 | yes |
8 | 2018 | 244711 | Newton | 0.984 | yes |
9 | 2019 | 271320 | The Castles of Burgundy | 0.984 | no |
10 | 2017 | 234487 | Altiplano | 0.984 | yes |
11 | 2018 | 244049 | Forum Trajanum | 0.984 | yes |
12 | 2016 | 200680 | Agricola (Revised Edition) | 0.983 | no |
13 | 2014 | 159508 | AquaSphere | 0.983 | yes |
14 | 2016 | 192945 | Coal Baron: The Great Card Game | 0.982 | yes |
15 | 2007 | 31260 | Agricola | 0.981 | yes |
16 | 2015 | 172385 | Porta Nigra | 0.979 | yes |
17 | 2014 | 159675 | Fields of Arle | 0.977 | yes |
18 | 2016 | 177736 | A Feast for Odin | 0.976 | yes |
19 | 2018 | 241831 | Reykholt | 0.975 | yes |
20 | 2014 | 157809 | Nations: The Dice Game | 0.974 | yes |
21 | 2017 | 233676 | Noria | 0.971 | yes |
22 | 2007 | 27173 | Vikings | 0.968 | yes |
23 | 2012 | 122515 | Keyflower | 0.968 | yes |
24 | 2008 | 34635 | Stone Age | 0.967 | yes |
25 | 2019 | 272682 | Expedition to Newdale | 0.966 | yes |
26 | 2013 | 102794 | Caverna: The Cave Farmers | 0.966 | yes |
27 | 2010 | 73439 | Troyes | 0.965 | yes |
28 | 2018 | 199792 | Everdell | 0.965 | no |
29 | 2012 | 121921 | Robinson Crusoe: Adventures on the Cursed Island | 0.965 | no |
30 | 2012 | 123260 | Suburbia | 0.963 | yes |
31 | 2013 | 136888 | Bruges | 0.962 | yes |
32 | 2014 | 148228 | Splendor | 0.962 | yes |
33 | 2019 | 286096 | Tapestry | 0.958 | yes |
34 | 2018 | 245934 | Carpe Diem | 0.957 | yes |
35 | 2018 | 247763 | Underwater Cities | 0.957 | yes |
36 | 2017 | 230933 | Merlin | 0.956 | yes |
37 | 2017 | 232988 | The Castles of Burgundy: The Dice Game | 0.955 | yes |
38 | 2016 | 193738 | Great Western Trail | 0.953 | yes |
39 | 2011 | 104006 | Village | 0.950 | yes |
40 | 2018 | 214887 | CO₂: Second Chance | 0.949 | yes |
41 | 2017 | 162886 | Spirit Island | 0.944 | yes |
42 | 2011 | 84876 | The Castles of Burgundy | 0.940 | yes |
43 | 2014 | 157354 | Five Tribes | 0.940 | yes |
44 | 2018 | 260428 | Pandemic: Fall of Rome | 0.940 | no |
45 | 2019 | 283863 | The Magnificent | 0.939 | yes |
46 | 2017 | 229265 | Wendake | 0.939 | no |
47 | 2016 | 193739 | Jórvík | 0.938 | yes |
48 | 2017 | 220308 | Gaia Project | 0.938 | yes |
49 | 2011 | 91873 | Strasbourg | 0.937 | yes |
50 | 2019 | 257066 | Sierra West | 0.937 | yes |
51 | 2017 | 214000 | In the Year of the Dragon: 10th Anniversary | 0.936 | no |
52 | 2014 | 132531 | Roll for the Galaxy | 0.936 | yes |
53 | 2017 | 220520 | Caverna: Cave vs Cave | 0.936 | yes |
54 | 1997 | 42 | Tigris & Euphrates | 0.935 | yes |
55 | 2013 | 143515 | Coal Baron | 0.934 | yes |
56 | 2017 | 201825 | Ex Libris | 0.934 | yes |
57 | 2018 | 240464 | Cosmic Run: Regeneration | 0.933 | yes |
58 | 2011 | 102680 | Trajan | 0.933 | yes |
59 | 2010 | 66505 | The Speicherstadt | 0.931 | yes |
60 | 2017 | 199383 | Calimala | 0.930 | yes |
61 | 2016 | 205418 | Agricola: Family Edition | 0.930 | no |
62 | 2015 | 172386 | Mombasa | 0.929 | yes |
63 | 2005 | 19857 | Glory to Rome | 0.928 | yes |
64 | 2018 | 236457 | Architects of the West Kingdom | 0.926 | yes |
65 | 2019 | 253635 | Ragusa | 0.924 | yes |
66 | 2007 | 25554 | Notre Dame | 0.924 | yes |
67 | 2017 | 197376 | Charterstone | 0.923 | yes |
68 | 2014 | 164928 | Orléans | 0.921 | yes |
69 | 2013 | 124361 | Concordia | 0.921 | yes |
70 | 2011 | 96848 | Mage Knight Board Game | 0.920 | yes |
71 | 2018 | 231581 | AuZtralia | 0.917 | no |
72 | 2019 | 270971 | Era: Medieval Age | 0.916 | yes |
73 | 2019 | 264052 | Circadians: First Light | 0.913 | yes |
74 | 2007 | 31594 | In the Year of the Dragon | 0.913 | yes |
75 | 2013 | 137408 | Amerigo | 0.911 | yes |
76 | 2018 | 256570 | Crown of Emara | 0.910 | yes |
77 | 2014 | 146886 | La Granja | 0.910 | yes |
78 | 2017 | 229220 | Santa Maria | 0.907 | yes |
79 | 2008 | 38453 | Space Alert | 0.906 | yes |
80 | 2011 | 90041 | Principato | 0.905 | yes |
81 | 2013 | 140620 | Lewis & Clark: The Expedition | 0.905 | yes |
82 | 2015 | 172381 | My Village | 0.902 | yes |
83 | 2014 | 148949 | Istanbul | 0.902 | yes |
84 | 2019 | 283948 | Marco Polo II: In the Service of the Khan | 0.901 | no |
85 | 2017 | 227789 | Heaven & Ale | 0.900 | yes |
86 | 2009 | 40831 | The Pillars of the Earth: Builders Duel | 0.900 | yes |
87 | 2018 | 223514 | Coin & Crown | 0.899 | no |
88 | 2016 | 193558 | The Oracle of Delphi | 0.898 | yes |
89 | 2016 | 192836 | The Colonists | 0.897 | yes |
90 | 2017 | 227515 | Riverboat | 0.896 | yes |
91 | 2013 | 52461 | Legacy: The Testament of Duke de Crecy | 0.894 | yes |
92 | 2007 | 31481 | Galaxy Trucker | 0.892 | yes |
93 | 2016 | 191977 | The Castles of Burgundy: The Card Game | 0.891 | yes |
94 | 2006 | 22141 | Cleopatra and the Society of Architects | 0.890 | yes |
95 | 2017 | 221194 | Dinosaur Island | 0.890 | yes |
96 | 2007 | 28143 | Race for the Galaxy | 0.889 | yes |
97 | 2016 | 176371 | Explorers of the North Sea | 0.889 | no |
98 | 2012 | 129948 | The Palaces of Carrara | 0.888 | yes |
99 | 2017 | 193031 | Coal Country | 0.887 | no |
100 | 2008 | 37380 | Roll Through the Ages: The Bronze Age | 0.883 | yes |
This section contains a variety of visualizations and metrics for assessing the performance of the model(s) during resampling. If you’re not particularly interested in predictive modeling, skip down further to the predictions from the model.
An easy way to examine the performance of classification model is to view a separation plot. We plot the predicted probabilities from the model for every game (from resampling) from lowest to highest. We then overlay a blue line for any game that the user does own. A good classifier is one that is able to separate the blue (games owned by the user) from the white (games not owned by the user), with most of the blue occurring at the highest probabilities (right side of the chart).
We can more formally assess how well each model did in resampling by looking at the area under the receiver operating characteristic curve. A perfect model would receive a score of 1, while a model that cannot predict the outcome will default to a score of 0.5. The extent to which something is a good score depends on the setting, but generally anything in the .8 to .9 range is very good while the .7 to .8 range is perfectly acceptable.
wflow_id | .metric | .estimator | .estimate |
GLM | roc_auc | binary | 0.93 |
Decision Tree | roc_auc | binary | 0.86 |
Another way to think about the model performance is to view its lift, or its ability to detect the positive outcomes over that of a null model. High lift indicates the model can much more quickly find all of the positive outcomes (in this case, games owned or played by the user), while a model with no lift is no better than random guessing. A gains chart is another way to view this.
While we are probably more interested in the lift provided by the models to evaluate their efficacy, we can also explore the optimal cutpoint if we wanted to define a hard threshold for identifying games a user will own vs not own.
The threshold we select depends on how we much we care about false positives (games the model predicts that the user does not own) vs false negatives (games the user owns that the model does not predict). We can toggle threshold to
Finally, we can understand the performance of the model by examining its calibration. If the model assigns a probability of 5%, how often does the outcome actually occur? A well calibrated model is one in which the predicted probabilities reflect the probabilities we would observe in the actual data. We can assess the calibration of a model by grouping its predictions into bins and assessing how often we observe the outcome versus how often our model expects to observe the outcome.
A model that is well calibrated will closely follow the dashed line - its expected probabilities match that of the observed probabilities. A model that consistently underestimates the probability of the event will be over this dashed line, be a while a model that overestimates the probability will be under the dashed line.
What games does the model think rahdo is most likely to own that are not in their collection?
Published | ID | Name | Pr(Owned) | Owned |
2019 | 271320 | The Castles of Burgundy | 0.984 | no |
2016 | 200680 | Agricola (Revised Edition) | 0.983 | no |
2018 | 199792 | Everdell | 0.965 | no |
2012 | 121921 | Robinson Crusoe: Adventures on the Cursed Island | 0.965 | no |
2018 | 260428 | Pandemic: Fall of Rome | 0.940 | no |
What games does the model think rahdo is least likely to own that are in their collection?
Published | ID | Name | Pr(Owned) | Owned |
2013 | 139771 | Star Trek: Attack Wing | 0.001 | yes |
2017 | 180845 | ELL deck | 0.002 | yes |
1983 | 438 | Scotland Yard | 0.004 | yes |
2002 | 5867 | 10 Days in Europe | 0.007 | yes |
2008 | 39856 | Dixit | 0.008 | yes |
Top 25 games most likely to be owned by the user in each year, highlighting in blue the games that the user has owned.
rank | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 |
1 | Keyflower | Glass Road | AquaSphere | 504 | Terraforming Mars | Altiplano | Newton | The Castles of Burgundy |
2 | Robinson Crusoe: Adventures on the Cursed Island | Caverna: The Cave Farmers | Fields of Arle | Porta Nigra | Agricola (Revised Edition) | Noria | Forum Trajanum | Expedition to Newdale |
3 | Suburbia | Bruges | Nations: The Dice Game | Mombasa | Coal Baron: The Great Card Game | Merlin | Reykholt | Tapestry |
4 | The Palaces of Carrara | Coal Baron | Splendor | My Village | A Feast for Odin | The Castles of Burgundy: The Dice Game | Everdell | The Magnificent |
5 | Agricola: All Creatures Big and Small | Concordia | Five Tribes | Viticulture Essential Edition | Great Western Trail | Spirit Island | Carpe Diem | Sierra West |
6 | Milestones | Amerigo | Roll for the Galaxy | Harbour | Jórvík | Wendake | Underwater Cities | Ragusa |
7 | Yedo | Lewis & Clark: The Expedition | Orléans | Grand Austria Hotel | Agricola: Family Edition | Gaia Project | CO₂: Second Chance | Era: Medieval Age |
8 | Terra Mystica | Legacy: The Testament of Duke de Crecy | La Granja | Kraftwagen | The Oracle of Delphi | Caverna: Cave vs Cave | Pandemic: Fall of Rome | Circadians: First Light |
9 | Il Vecchio | Rococo | Istanbul | The Pursuit of Happiness | The Colonists | In the Year of the Dragon: 10th Anniversary | Cosmic Run: Regeneration | Marco Polo II: In the Service of the Khan |
10 | Tzolk'in: The Mayan Calendar | Sail to India | Roll Through the Ages: The Iron Age | Through the Ages: A New Story of Civilization | The Castles of Burgundy: The Card Game | Ex Libris | Architects of the West Kingdom | Nova Luna |
11 | CO₂ | City of Remnants | Praetor | OctoDice | Explorers of the North Sea | Calimala | AuZtralia | Tiny Towns |
12 | Space Cadets | Asante | Subdivision | The Voyages of Marco Polo | Covert | Charterstone | Crown of Emara | Masters of Renaissance: Lorenzo il Magnifico – The Card Game |
13 | Snowdonia | Rialto | Imperial Settlers | Raiders of the North Sea | Quadropolis | Santa Maria | Coin & Crown | Herbaceous Sprouts |
14 | Escape: The Curse of the Temple | Bremerhaven | Patchwork | Queen's Architect | Citadels | Heaven & Ale | Dice Settlers | Maracaibo |
15 | Clash of Cultures | Cinque Terre | Onirim (Second Edition) | 7 Wonders Duel | Aeon's End | Riverboat | Duelosaur Island | Revolution of 1828 |
16 | The Great Zimbabwe | Euphoria: Build a Better Dystopia | Port Royal | Arboretum | Fields of Green | Dinosaur Island | Passing Through Petra | Clank!: Legacy – Acquisitions Incorporated |
17 | Ginkgopolis | Thunderstone Advance: Numenera | Akrotiri | Isle of Skye: From Chieftain to King | Arkham Horror: The Card Game | Coal Country | Coimbra | Paladins of the West Kingdom |
18 | Targi | Spyrium | Castles of Mad King Ludwig | Valley of the Kings: Afterlife | 51st State: Master Set | Notre Dame: 10th Anniversary | Grasse | Wingspan |
19 | New Amsterdam | Rogue Agent | La Isla | Coffee Roaster | Honshū | Kitchen Rush | Concordia Venus | Caylus 1303 |
20 | Love Letter | Relic Runners | Valley of the Kings | Lanterns: The Harvest Festival | Martians: A Story of Civilization | Lisboa | Gunkimono | Islands in the Mist |
21 | Among the Stars | Bora Bora | Kanban: Driver's Edition | Copper Country | La Granja: No Siesta | Clans of Caledonia | Founders of Gloomhaven | Egizia: Shifting Sands |
22 | Tokaido | Bruxelles 1893 | Power Grid Deluxe: Europe/North America | Minerva | Black Orchestra | Gloomhaven | Tales of the Northlands: The Sagas of Noggin the Nog | Century: A New World |
23 | Archipelago | The Witches: A Discworld Game | Panamax | Rome: City of Marble | Cottage Garden | Yamataï | Gingerbread House | Barrage |
24 | Copycat | Citrus | Pandemic: The Cure | Bastion | Niña & Pinta | Sagrada | Key Flow | The Isle of Cats |
25 | Le Havre: The Inland Port | Patchistory | Grog Island | Discoveries: The Journals of Lewis & Clark | Hellas | Fast Forward: FLEE | New Frontiers | Last Bastion |
This is an interactive table for the model’s predictions for the training set (from resampling).
We’ll validate the model by looking at its predictions for games published in 2020. That is, how well did a model trained on a user’s collection through 2020 perform in predicting games for the user in 2020?
username | outcome | dataset | method | .metric | .estimate |
rahdo | owned | validation | GLM | roc_auc | 0.861 |
rahdo | owned | validation | Decision Tree | roc_auc | 0.775 |
Table of top 50 games from 2020, highlighting games that the user owns.
Published | ID | Name | Pr(Owned) | Owned |
2020 | 318983 | Faiyum | 0.987 | yes |
2020 | 300322 | Hallertau | 0.987 | yes |
2020 | 304420 | Bonfire | 0.983 | yes |
2020 | 184267 | On Mars | 0.981 | no |
2020 | 300327 | The Castles of Tuscany | 0.967 | yes |
2020 | 233262 | Tidal Blades: Heroes of the Reef | 0.925 | no |
2020 | 296151 | Viscounts of the West Kingdom | 0.917 | yes |
2020 | 308765 | Praga Caput Regni | 0.906 | yes |
2020 | 306040 | Merv: The Heart of the Silk Road | 0.886 | yes |
2020 | 296100 | Rococo: Deluxe Edition | 0.878 | yes |
2020 | 306481 | Tawantinsuyu: The Inca Empire | 0.872 | yes |
2020 | 310442 | Feierabend | 0.863 | yes |
2020 | 293556 | Gloomy Graves | 0.852 | no |
2020 | 284742 | Honey Buzz | 0.852 | no |
2020 | 301880 | Raiders of Scythia | 0.847 | yes |
2020 | 267009 | Rome & Roll | 0.846 | no |
2020 | 269810 | Nevada City | 0.846 | yes |
2020 | 301716 | Glasgow | 0.839 | yes |
2020 | 265784 | Cleopatra and the Society of Architects: Deluxe Edition | 0.832 | no |
2020 | 312804 | Pendulum | 0.828 | yes |
2020 | 316412 | The LOOP | 0.823 | yes |
2020 | 313698 | Monster Expedition | 0.797 | no |
2020 | 302310 | Nanaki | 0.786 | no |
2020 | 291457 | Gloomhaven: Jaws of the Lion | 0.760 | no |
2020 | 298065 | Santa Monica | 0.728 | yes |
2020 | 291508 | Tiny Epic Dinosaurs | 0.707 | no |
2020 | 295486 | My City | 0.699 | yes |
2020 | 298371 | Wild Space | 0.694 | no |
2020 | 312484 | Lost Ruins of Arnak | 0.688 | yes |
2020 | 311193 | Anno 1800 | 0.687 | yes |
2020 | 282954 | Paris | 0.682 | yes |
2020 | 283155 | Calico | 0.680 | yes |
2020 | 320819 | Dinner in Paris | 0.667 | no |
2020 | 316377 | 7 Wonders (Second Edition) | 0.658 | yes |
2020 | 293678 | Stellar | 0.657 | yes |
2020 | 317985 | Beyond the Sun | 0.656 | yes |
2020 | 314040 | Pandemic Legacy: Season 0 | 0.654 | no |
2020 | 300001 | Renature | 0.642 | yes |
2020 | 279537 | The Search for Planet X | 0.638 | no |
2020 | 325555 | Cantaloop: Book 1 – Breaking into Prison | 0.630 | no |
2020 | 284217 | Rush M.D. | 0.626 | yes |
2020 | 281466 | Yedo: Deluxe Master Set | 0.625 | no |
2020 | 284378 | Kanban EV | 0.611 | no |
2020 | 307844 | Atheneum: Mystic Library | 0.604 | yes |
2020 | 313349 | Indus 2500 BCE | 0.593 | yes |
2020 | 317105 | Tiny Epic Galaxies BLAST OFF! | 0.588 | no |
2020 | 282922 | Windward | 0.587 | no |
2020 | 292333 | Cowboys II: Cowboys & Indians Edition | 0.583 | no |
2020 | 302723 | Forgotten Waters | 0.571 | yes |
2020 | 296626 | Sonora | 0.563 | yes |
We can then refit our model to the training and validation set in order to predict all upcoming games for the user.
Examine the top 100 upcoming games, highlighting in blue ones the user already owns.
Rank | Published | ID | Name | Pr(Owned) | Owned |
1 | 2021 | 343905 | Boonlake | 0.998 | yes |
2 | 2022 | 314582 | Amsterdam | 0.993 | no |
3 | 2022 | 314580 | Hamburg | 0.990 | no |
4 | 2022 | 346645 | New York City | 0.988 | no |
5 | 2022 | 341945 | La Granja: Deluxe Master Set | 0.984 | no |
6 | 2023 | 349793 | Age of Rome | 0.955 | no |
7 | 2021 | 342942 | Ark Nova | 0.954 | yes |
8 | 2021 | 249277 | Brazil: Imperial | 0.914 | no |
9 | 2021 | 298378 | Maharaja | 0.912 | no |
10 | 2022 | 302892 | Frozen Frontier | 0.910 | no |
11 | 2023 | 331820 | Rolling Heights | 0.891 | no |
12 | 2021 | 344277 | Corrosion | 0.876 | yes |
13 | 2021 | 304783 | Hadrian's Wall | 0.875 | no |
14 | 2022 | 331106 | The Witcher: Old World | 0.867 | no |
15 | 2021 | 332944 | Sobek: 2 Players | 0.864 | no |
16 | 2022 | 317511 | Tindaya | 0.861 | no |
17 | 2021 | 329593 | Settlement | 0.848 | no |
18 | 2021 | 300523 | Biblios: Quill and Parchment | 0.845 | no |
19 | 2021 | 238799 | Messina 1347 | 0.842 | yes |
20 | 2021 | 315234 | Embarcadero | 0.839 | no |
21 | 2022 | 349067 | The Lord of the Rings: The Card Game – Revised Core Set | 0.838 | no |
22 | 2021 | 292899 | Tribune | 0.827 | no |
23 | 2021 | 339484 | Savannah Park | 0.823 | yes |
24 | 2021 | 283387 | Rocketmen | 0.823 | no |
25 | 2022 | 342810 | Marrakesh | 0.813 | no |
26 | 2022 | 342674 | Jiangnan: Life of Gentry | 0.812 | no |
27 | 2021 | 331787 | Tiny Epic Dungeons | 0.811 | no |
28 | 2022 | 319348 | Magna Roma | 0.809 | no |
29 | 2021 | 295947 | Cascadia | 0.806 | yes |
30 | 2022 | 311988 | Frostpunk: The Board Game | 0.793 | no |
31 | 2022 | 348070 | The Palaces of Carrara (Second Edition) | 0.793 | no |
32 | 2022 | 266018 | Trinidad | 0.792 | no |
33 | 2021 | 283242 | The Whatnot Cabinet | 0.785 | yes |
34 | 2021 | 298069 | Cubitos | 0.784 | yes |
35 | 2021 | 298102 | Roll Camera!: The Filmmaking Board Game | 0.781 | yes |
36 | 2022 | 324894 | Free Radicals | 0.777 | yes |
37 | 2022 | 265298 | Aquanauts | 0.775 | no |
38 | 2021 | 260524 | Beyond Humanity: Colonies | 0.773 | no |
39 | 2021 | 277700 | Merchants Cove | 0.771 | no |
40 | 2022 | 352201 | Skull Canyon: Ski Fest | 0.768 | no |
41 | 2022 | 305096 | Endless Winter: Paleoamericans | 0.767 | no |
42 | 2022 | 305462 | The Age of Atlantis | 0.765 | no |
43 | 2022 | 266064 | Trudvang Legends | 0.762 | no |
44 | 2022 | 347703 | First Rat | 0.760 | no |
45 | 2022 | 310873 | Carnegie | 0.756 | no |
46 | 2021 | 342848 | World of Warcraft: Wrath of the Lich King | 0.755 | no |
47 | 2021 | 281248 | Cape May | 0.741 | no |
48 | 2021 | 289550 | Lions of Lydia | 0.740 | yes |
49 | 2021 | 328286 | Mission ISS | 0.736 | no |
50 | 2021 | 341169 | Great Western Trail (Second Edition) | 0.733 | yes |
51 | 2021 | 252752 | Genotype: A Mendelian Genetics Game | 0.729 | yes |
52 | 2021 | 339789 | Welcome to the Moon | 0.724 | yes |
53 | 2021 | 325698 | Juicy Fruits | 0.721 | yes |
54 | 2021 | 333553 | For the King (and Me) | 0.720 | no |
55 | 2022 | 319807 | Shogun no Katana | 0.718 | no |
56 | 2022 | 328124 | Bot Factory | 0.715 | no |
57 | 2021 | 344768 | Mobile Markets: A Smartphone Inc. Game | 0.712 | yes |
58 | 2022 | 356033 | Libertalia: Winds of Galecrest | 0.705 | no |
59 | 2022 | 352695 | Oranienburger Kanal | 0.701 | no |
60 | 2021 | 328479 | Living Forest | 0.698 | no |
61 | 2022 | 343927 | Union Stockyards | 0.698 | no |
62 | 2022 | 342046 | Phraya | 0.696 | no |
63 | 2022 | 294702 | Tenpenny Parks | 0.695 | no |
64 | 2022 | 322565 | Silicon Valley | 0.682 | no |
65 | 2021 | 332290 | Stardew Valley: The Board Game | 0.682 | no |
66 | 2021 | 339906 | The Hunger | 0.678 | yes |
67 | 2021 | 322195 | Kokopelli | 0.670 | yes |
68 | 2021 | 309319 | Apogee | 0.667 | no |
69 | 2022 | 258779 | Planet Unknown | 0.666 | no |
70 | 2021 | 316786 | Tabannusi: Builders of Ur | 0.661 | yes |
71 | 2022 | 359764 | Shake That City | 0.656 | no |
72 | 2021 | 332386 | Brew | 0.646 | yes |
73 | 2021 | 341048 | Free Ride | 0.643 | no |
74 | 2022 | 323707 | MOB: Big Apple | 0.633 | no |
75 | 2021 | 298383 | Golem | 0.632 | yes |
76 | 2023 | 312682 | Silver Coin: Age of Monster Hunters | 0.632 | no |
77 | 2021 | 324242 | Sheepy Time | 0.630 | yes |
78 | 2021 | 299684 | Khôra: Rise of an Empire | 0.628 | yes |
79 | 2021 | 302510 | Mining Colony | 0.622 | no |
80 | 2021 | 297563 | Faraway Valley | 0.618 | no |
81 | 2022 | 326945 | Castles of Mad King Ludwig: Collector's Edition | 0.617 | no |
82 | 2021 | 310198 | Escape: Roll & Write | 0.617 | yes |
83 | 2021 | 317457 | Dinosaur World | 0.615 | yes |
84 | 2021 | 340455 | King of the Valley | 0.608 | no |
85 | 2021 | 322588 | Origins: First Builders | 0.606 | yes |
86 | 2021 | 315937 | X-Men: Mutant Insurrection | 0.604 | yes |
87 | 2022 | 351097 | Townies | 0.597 | no |
88 | 2021 | 306202 | Philosophia: Floating World | 0.594 | no |
89 | 2021 | 343526 | G.I. JOE Deck-Building Game | 0.593 | yes |
90 | 2022 | 280726 | Legacies | 0.591 | no |
91 | 2022 | 345088 | Founders of Teotihuacan | 0.589 | yes |
92 | 2022 | 344620 | Pocket Master Builder | 0.588 | no |
93 | 2021 | 322622 | Floriferous | 0.587 | yes |
94 | 2023 | 304510 | Pampero | 0.572 | no |
95 | 2022 | 331190 | Meeples & Monsters: Kickstarter Edition | 0.571 | no |
96 | 2022 | 284189 | Foundations of Rome | 0.570 | no |
97 | 2021 | 285036 | Shadow Kingdoms of Valeria | 0.565 | yes |
98 | 2021 | 328871 | Terraforming Mars: Ares Expedition | 0.558 | yes |
99 | 2021 | 329465 | Red Rising | 0.557 | yes |
100 | 2022 | 256997 | Perseverance: Castaway Chronicles – Episodes 1 & 2 | 0.554 | yes |